Private AI vs cloud AI: how to choose
A practical comparison for businesses that handle confidential information.
The short answer
Cloud AI is convenient and fine for non-sensitive work. Private, on-premises AI is worth considering when the data is confidential, regulated or commercially sensitive, because it keeps processing inside your own environment.
Side-by-side
| Cloud AI | Private on-premises AI | |
|---|---|---|
| Where data is processed | Provider’s servers | Your hardware |
| Internet needed | Yes | No, when deployed offline |
| Pricing model | Usually per user or per use | Project and support, no per-seat AI subscription |
| Control over updates | Provider decides | You approve and apply them |
| Upfront effort | Low | Higher, with hardware and setup |
| Best for | General, non-sensitive tasks | Confidential, regulated or proprietary data |
When cloud AI is fine
Drafting public marketing copy, brainstorming and researching public information carry little risk. Even then, set a workplace AI policy so staff know what must never be pasted in.
When to choose a local agent
Consider private AI if staff handle client financials, privileged files, patient or employee records, bids and pricing, or designs. It suits teams that want AI answers drawn from their own documents without the data leaving the building.
Questions to ask any AI vendor
- Where is my data processed and stored?
- Is my data used to train models?
- How long is it retained, and how is it deleted?
- Who has access, and is there an audit trail?
- Which subprocessors are involved?
- What happens to my data if I leave?
We answer these for our own deployments in our cybersecurity approach. See also the FAQ or how a local AI agent works.
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